Research

C. elegans, engineering, and systems biology

The San Miguel Lab is dedicated to accelerating biological discoveries by incorporating engineering and systems approaches to answer elusive questions in different areas of biology. We focus on applying engineering tools to perform experiments unfeasible with traditional techniques. We use the nematode C. elegans as a model organism and we work in topics such as neuronal aging, synaptic plasticity, noise and stochasticity, genetic networks, and buffering, among others. We incorporate tools that enable large-scale high-content quantitative characterization of phenotypes at various scales: from the subcellular level all the way to whole-organism behavioral outputs. We use custom-built platforms for our experimental studies, which typically incorporate microfluidics, computer vision, statistical data analysis, and integrative automation and control.

C. elegans as a model organism has been studied extensively throughout past years. However, conventional techniques used to study these nematodes is low-throughput, labor intensive, and in some cases unable to perform certain experiments such as lifelong imaging. In my project, I am implementing microfluidic devices to address the issues mentioned above. My project is focused on designing and fabricating a novel microfluidic device to perform high-resolution, longitudinal imaging on the same population of nematodes throughout their life span without using immobilizing or reproduction-inhibiting drugs. The goal of this project is to track subtle changes within nervous system as nematode ages. We are interested in investigating synaptic variation such as synaptic localization and synaptic plasticity within worm’s life span. Neuronal alteration is also a phenotype which would be studied within nematode’s life span. In these experiments, we are going to use wild-type strains as well as various mutants.

Though it is a natural phase of every human life, very little is known about the molecular mechanisms that play a role in the process of aging. While it is both practically and ethically challenging to study aging directly in humans, the nematode C. elegans has emerged as a model organism that is both simple and highly representative of human genetic networks. Our goal is to identify mutations in C. elegans which yield aging-dependent phenotypes. This will be done by screening for these phenotypes in a population of worms that underwent random mutagenesis. Due to complications involved with conventional methods of screening for random mutants, we are developing a microfluidic platform to identify candidate worms with phenotypes of interest by measuring the phenotype over the worm’s lifetime. The platform will allow for the retrieval of each candidate worm’s progeny in a simple and straightforward manner, and its operation will be automated, yielding large sets of data in a relatively short time. Using this platform, we anticipate forming a clearer picture of the molecular mechanisms behind aging phenotypes, such as lifespan, and reduction in locomotion, mechanosensation, and chemotaxis. We also aim to adapt the platform to be compatible with higher resolution imaging, allowing for the measurement of phenotypes at the scale of neuronal structure. This will allow us to further understand the mechanisms behind neurodegenerative diseases, such as Alzheimer’s disease.

Microscopy, visual screens, and phenotyping are frequently applied to model organisms in combination with genetics. Although widely reported, these techniques for multicellular organisms have mostly remained manual, cumbersome, and low-throughput. Our goal is to develop a microfluidic platform with complete automation of sample handling and positioning, phenotyping, and high resolution imaging of Caenorhabditis elegans, under controlled environmental or drug environments. The engineered microfluidic device will be coupled with customized software, to enable us to perform high-throughput, high-resolution microscopy with minimum human intervention and can be utilized with any microscopy setup. The microfluidic platform would be capable of robust fine spatial and temporal control, self-regulated sample-loading and automatic sample-positioning, while the integrated software performs imaging and classification of worms based on morphological features, quantitative characterization of health span metrics, and multi-color fluorescence imaging of aging networks. The proposed microfluidic device will allow us to identify optimal environmental perturbation regimes to maximize life span and health span, while characterizing the spatiotemporal responses of key aging networks hubs.

The activity of gene networks associated with life span and health span varies in space and time, and can be perturbed by changes in the environment. It is still unclear how the history of these perturbations, and the responses of aging-associated gene networks determines the health span and lifespan of the C. elegans nematode. The longitudinal in vivo tracking of these live perturbations can be achieved through quantitative imaging processing of endogenous gene network expression. To accomplish this goal, we will combine microfluidics, high throughput imaging, and multi-labeled endogenous gene expression lines (generated through CRISPR). A microfluidic device designed ad hoc for in vivo tracking of C. elegans populations will allow quantitative imaging of fluorescent gene expression related to reproduction, dietary restriction, heat shock, oxidative stress, etc. These data sets will be used to model and predict the relationships between environmental conditions and the gene networks governing the aging process in the model organism.

My work involves designing a high throughput platform to analyze the role that insulin-like-peptides (ILPs) play in the behavior of C. elegans. These ILPs have been shown to influence various developmental and physiological processes, including lifespan and neural plasticity, but the specific roles of many of these peptides remain unknown. This platform will allow for the quantitative analysis of movement, a downstream output of the nervous system, of a large number of individuals. It will be used to analyze the change in behavioral output of C. elegans having silenced expression of each one of the forty ILPs by use of RNAi. Videos of swimming animals are acquired and analyzed by using customized code in Matlab to quantify the differences in swimming behavior.

We are trying to understand the connections between neuronal exercise and synaptic function and plasticity. To answer this question, we are designing and testing a platform to perform controlled optogenetic activation of C. elegans motor neurons by LED illumination. We are working on automating LED flashes, imaging, and data analysis. With this improved platform, we are looking to further study the effect of increased flash length on contractions, lag time between flash and contraction, and muscular response in liquid media. Other areas of interest include: response of uncoordinated C. elegans as well as populations of aging animals. In the future, we will couple these experiments with high-resolution imaging of synaptic patterns. Ultimately, we’re aiming to quantify how plastic synapses are (morphologically and functionally), under different conditions and under various neuronal exercise regimes.